The present invention relates to optical analysis systems and, in particular, systems and methods that employ optical analysis systems to inspect and monitor the internals of a pipeline.
In the oil and gas industry, a tool known as a “pig” refers to any of a variety of movable inline inspection devices that are introduced into and conveyed (e.g., pumped, pushed, pulled, self-propelled, etc.) through a pipeline or a flow line. Pigs often serve various basic functions while traversing the pipeline, including cleaning the pipeline to ensure unobstructed fluid flow and separating different fluids flowing through the pipeline. Modern pigs, however, can be highly sophisticated instruments that include electronics and sensors employed to collect various forms of data during the trip through the pipeline. Such pigs, often referred to as smart pigs or inline inspection pigs, can be configured to inspect the internals or interior of the pipeline, and capture and record specific geometric information relating to the sizing and positioning of the pipeline at any given point along the length thereof. Smart pigs can also be configured to determine pipe wall thickness and pipe joint weld integrity with the appropriate sensing equipment.
Smart pigs, which are also referred to as inline inspection tools, typically use technologies such as magnetic flux leakage (MFL) and electromagnetic acoustic transducers to detect surface pitting, corrosion, cracks, and weld defects in steel/ferrous pipelines. Acoustic resonance technology and ultrasonics have also been employed to detect various aspects and defects of a pipeline. After a pigging run has been completed, positional data recorded from various external sensors is combined with the pipeline evaluation data (corrosion, cracks, etc.) derived from the pig to generate a location-specific defect map and characterization. The combined data is useful in determining the general location, type, and size of various types of pipe defects. The data can also be used to judge the severity of the defects and help repair crews locate and repair the defects.
While conventional smart pigs are generally able to locate various pipeline defects, they are, for the most part, unable to provide adequate reasons as to why the particular defect is occurring or has occurred. For instance, pipeline corrosion can develop for a myriad of reasons, including the presence of acids or other caustic substances and chemicals flowing within the pipeline. Knowing “why” the corrosion or other event is occurring, may prove advantageous to an operator in stopping or otherwise reversing the corrosive effects.
Also, conventional smart pigs are largely unable to efficiently monitor the formation of both organic and inorganic deposits detected in pipelines and flow lines. Typically, the analysis of such deposits is conducted off-line using laboratory analyses, such as spectroscopic and/or wet chemical methods, which analyze an extracted sample of the fluid. Although off-line, retrospective analyses can be satisfactory in certain cases, but they nonetheless do not allow real-time or near real-time analysis capabilities but instead often require hours to days to complete the analysis. During the lag time between collection and analysis, the characteristics of the extracted sample of the chemical composition oftentimes changes, thereby making the properties of the sample non-indicative of the true chemical composition or characteristic. Efficiently and accurately identifying organic and inorganic deposits in pipelines could prove advantageous to pipeline operators in mitigating costly corrective action. Moreover, accurately identifying the concentration of such deposit buildups in pipelines may provide valuable information on the effectiveness of treatments designed to counteract the deposits.